The way states reported testing information was dictated by these difficulties they faced in collecting it, and because each state had slightly different weak spots, reporting was unstandardized. Some states reported just electronically transmitted lab results, while others reported faxed data too. Some states reported antigen tests (or early on, antibody tests) combined with PCR-test data, some separated them out, and some states didn’t report them at all. Race and ethnicity data were highly incomplete and unstandardized, impeding efforts to understand the pandemic’s disproportionate effect on Black, Latino, and Indigenous communities. Of all the inconsistencies across states, one extraordinarily daunting problem that did improve over the course of the pandemic was the variation in testing units. For much of the pandemic, some states chose (or had only the capability) to count the number of unique people tested rather than the number of tests conducted. Because individuals are likely to receive multiple tests for COVID-19 over time, states counting people rather than tests appeared to be doing much less testing than others, throwing off measures used to contextualize case counts, such as test positivity. By the end of our data collection, all but two jurisdictions had standardized counting tests rather than people—although there are still some variations within how states count tests. Only the CDC ever stood a chance at collecting testing data that were standardized across jurisdictions. But the federal government has faced its own share of problems in putting together a national testing data set. When federal testing data were first published last May, many states still had not started submitting data to CELR, leading to a data set that was highly divergent from state data because it had different sourcing. And even now, with every state onboarded to CELR, many states show persistent data-quality issues in their federally published data, which have caused continued disparities with their state-published data.